Projets novateurs réalisés

Development of Low-Loss, High-Finesse Nanofiber Optical Resonators for Distributed Quantum Computing

There is a significant global effort to develop fault-tolerant quantum computers, with a leading strategy being the creation of modular, distributed quantum networks. This approach requires high-fidelity “quantum interconnects” to link individual quantum processors. This project proposes to fabricate and optimize the fundamental component for these interconnects: ultra-low-loss, high-finesse nanofiber optical resonators. This will be achieved by using the specialized heat-and-pull fabrication process pioneered at Waseda University. These high-quality resonators are essential hardware for future scalable quantum computers and networks. Both Concordia University and Waseda University will benefit from the project. Concordia will gain direct access to Waseda’s world-class facilities and the critical know-how of this fabrication technique, which is currently unavailable at the home institution. Waseda University will benefit from the intern’s direct contributions to their ongoing research in nanofiber optimization, which is part of a national-level JST Moonshot program. This project will establish a new, foundational collaboration, paving the way for future joint publications and international projects.

L2M – Integrated Data Science Platform for Complex Spatiotemporally Resolved Biomedical Applications

Reliable annotations set critical ground truths for modern data science initiatives. In life sciences, however, large volumes of physiologic data streams produce computational bottlenecks that hinder this workflow. A researcher’s only viable alternative is to adopt a DIY approach, exporting data to separate coding environments. This fragments the analysis from the visual context and corrodes scientific impact due to a lack of standardization and reproducibility.

To address this, we offer an interactive analysis platform specializing in large physiologic data streams. The software utilizes multi-resolution charting to enable instant visualization of massive datasets and features a dedicated annotation management system to ensure rigorous, standardized labeling. Uniquely, it integrates directly with user-configured IDEs to merge visualization with real-time code experimentation.

This project is positioned to capture a widening market gap. While the post-ChatGPT AI boom created vast tooling ecosystems for enterprise data science, academic and independent researchers remain underserved by rigid, incumbent tools. Through this internship, the intern will validate product-market fit to capture this high-value research market. Supported by North Forge, this project aims to accelerate the commercialization of Canadian intellectual property, fostering economic development by delivering a solution that restores precision and scalability to physiological research.

Metis Family Services – Digital Transformation of HR File Systems: Designing and Implementing a Compliant HRIS

Métis Family Services is a delegated child and family services agency that provides culturally grounded safety, support, and community services to Métis children, youth, and families across Surrey and the Greater Vancouver region. As the organization expands its programming and workforce, it faces a critical innovation challenge: the transition from a paper-based human resources file system to a fully digital, compliant, and configurable Human Resource Information System (HRIS). The current physical HR file structure limits operational efficiency, data accuracy, and timely access to information across departments, creating barriers to evidence-based decision-making, workforce planning, and organizational growth. Because this transformation requires a comprehensive review of existing processes, analysis of gaps, configuration of a customized HRIS, and development of a structured transition plan, the work goes far beyond routine administrative duties. Instead, the project requires applied research, system evaluation, and the design of new digital workflows that will fundamentally improve how the agency manages employee information. This innovation initiative demands expertise in HRIS systems, data management, change management, business process mapping, compliance requirements, and the ability to translate technical system configurations into practical, user-friendly tools for staff. By conducting a detailed review of current HR file practices, identifying pain points, redesigning digital file structures, and configuring a customized HRIS solution, the intern will help Métis Family Services modernize its HR infrastructure in a way that enhances data integrity, supports organizational accountability, and strengthens long-term service delivery capacity.

Évaluation des impacts de la déconnexion numérique

Le “digital free tourism” (tourisme déconnecté ou déconnexion numérique en milieu touristique) désigne une forme de tourisme où les personnes voyageuses peuvent se déconnecter des technologies numériques (téléphones intelligents, médias sociaux, etc.) pendant leur séjour. Certains travaux récents questionnent cependant les limites du tourisme déconnecté, en soulignant par exemple le stress vécu à la suite d’une déconnexion imposée ou encore les tensions/ambivalences qui naissent entre le besoin de se déconnecter et celui de rester connecté pour des raisons pratiques ou sociales. Dans ce contexte, l’Association Hôtellerie du Québec (AHQ) et le Manoir d’Youville font appel à la Chaire de recherche sur les dépendances comportementales et la réduction des méfaits du Centre de recherche médicale de l’Université de Sherbrooke pour étudier l’état de la déconnexion numérique ainsi que les impacts associés. Qu’est-ce que la littérature dit sur le sujet? Est-ce une pratique efficace? Quelles sont les stratégies mises en place, à ce jour, par les acteurs du milieu touristique au Québec, au Canada et ailleurs?

Understanding and improving compositional generalization in vision-language models

Compositionality — the ability to understand new combinations of familiar parts — is a core aspect of human cognition and reasoning, but current vision-language models such as CLIP still struggle with it. These limitations reduce the reliability of systems that must correctly interpret objects, attributes, and relations in real-world scenarios. Although many methods have been proposed to strengthen CLIP’s compositional abilities, it remains unclear which parts of the model they affect or why certain approaches lead to better results. This project will develop a standardized diagnostic framework to identify where compositional behaviour improves within the models and what factors drive those improvements. The resulting insights and tools will help guide the development of more reliable multimodal AI systems. This project will benefit both participating institutions by supporting their shared interests in advancing reliable, scalable AI methods, fostering a new research collaboration between the groups, and creating reusable resources that will support future research and student training.

Application of Advanced Oxidation Processes for Removing Emerging Contaminants, with a Focus on Anticancer Pharmaceuticals and PFAS from Water

This project focuses on the removal of emerging contaminants (ECs), including anticancer pharmaceuticals and PFAS, from water using advanced oxidation processes such as photocatalysis and UV-based treatments.It will explore how the molecular structures of these persistent pollutants influence their degradation pathways and the formation of transformation by-products. The internship integrates Concordia University’s environmental engineering expertise with the University of Gdansk’s advanced laboratory facilities to enable systematic experimentation, detailed chemical analysis, and optimized treatment development. This collaboration will improve scientific understanding of ECs degradation, provide the intern with hands-on experience in analytical and experimental facilities unavailable at Concordia, and support the timely completion of the PhD thesis. For both institutions, the project strengthens international research partnerships, produces high-quality data for joint publications, enhances capacity in sustainable water treatment, and fosters knowledge exchange between Canadian and European teams.

Analyzing Driver Reaction Times in Vehicle-Pedestrian Interactions Through Simulator-Based Experiments

The proposed research focuses on improving road safety by studying how drivers react when encountering pedestrians in mixed traffic conditions. While most existing studies emphasize pedestrian behavior, little is known about how drivers respond in these situations. To address this gap, the project will use a driving simulator that replicates a real 5.5 km road section to observe driver actions during simulated pedestrian interactions under different traffic conditions. Key behaviors, such as slowing down, braking, or maintaining speed, will be measured using various performance indicators like speed, braking force, and reaction times. Advanced modeling techniques will then identify patterns in driver behavior, which will be validated through real-world driving experiments. For the partner organization, 30 Forensic Engineering, this research offers valuable insights for accident reconstruction, root cause analysis, and understanding human factors in collisions. These findings can enhance the accuracy of forensic investigations, support expert testimony, and inform the design of safer road environments and driver assistance systems. Ultimately, this collaboration will strengthen evidence-based solutions that reduce pedestrian-related accidents, improve liability assessments, and contribute to safer communities.

Temperature-Dependent Raman Spectroscopic Investigation of High-Performance Bi(Zn1/2Ti1/2)O3 -PbTiO3–BiScO3 Piezo/-Ferroelectric Single Crystals

This project aims to develop new high-performance materials that can operate reliably in extreme environments, such as jet engines, nuclear reactors, and the automotive industry. Many modern technologies rely on piezoelectric and ferroelectric materials, which convert mechanical energy into electrical energy and vice versa. However, most of today’s materials lose performance at high temperatures, limiting their use in advanced industrial applications.
To address this challenge, the project investigates a promising class of bismuth-based perovskite single crystals. These materials exhibit strong electrical performance and unusual “relaxor” behavior, but the origins of this behavior are still not well understood. Gaining insight into their structure is essential for designing next-generation high-temperature devices.
At Simon Fraser University (SFU), single crystals will be grown and tested to evaluate their functional properties. The project will then continue at the University of Hamburg, where advanced temperature-dependent Raman spectroscopy— not available at SFU—will be used to study how the atomic structure evolves with temperature. These measurements will reveal how local lattice distortions influence the material’s electrical response.
This international collaboration will deepen our understanding of high-temperature functional materials, support the development of more efficient technologies, and strengthen Canada’s research capacity in advanced materials.

Mineral chemistry as a tool for exploration – insights from the Kinkaid project, Nevada

This study will investigate the potential to use mineral chemistry to develop vectors around poorly understood Au and Cu mineralization in Nevada. We will combine traditional mapping methods with state-of-theartmineral chemistry techniques to assess the alteration halo around a complex array of mineralized systems. The research will be completed by a master’s students, who will be trained in advanced research methods, making them highly skilled assets for industry, academia, or government surveys. This study has the potential to lead to new discoveries by developing tools that can be used to vector towards mineralisation in covered terranes that can be applied elsewhere within Canada and by Canadian companies working overseas. At a broader scale, the tools generated by this project will help Canadian mining companies enhance exploration efficiency and reduce both the time and capital cost for the discovery of mineral resources.

Organic gunshot residue as forensic evidence

Organic gunshot residue (OGSR) is a trace residue released during firearm discharge. It includes unburned, partially burned, and pyrolyzed components of the propellant (smokeless powder) and other organic substances (stabilizers, plasticizers, flame suppressants). Recently, the forensic community has shown interest in complementing standard SEM-EDS methods for the detection of inorganic gunshot residue (IGSR), with analytical methods that can detect the organic constituents. Unlike IGSR, which consists mainly of microscopic particles released from the primer (i.e., Pb, Ba, Sb), OGSR offers direct evidence related to the propellant formulation. The main components yielding OGSR are the stabilizers, like diphenylamine (DPA), ethyl centralite (EC), and akardite (AKII)), and the energetic explosives, like nitroglycerin (NG)) and nitrocellulose (NC) used in the smokeless powder (SP). In this study, we hypothesize that partially burnt and neat smokeless powders will exhibit different stability and degradation products. Monitoring these products using mass spectrometry methods can expand the scope of current analytical OGSR detection and provide insights into the stability of these residues recovered from forensic substrates (skin, clothing, etc.).

Mining and Modeling Review-Priority Labels in Gerrit for Predictive Review Analytics

Code review is a critical step in modern software development, ensuring quality, preventing defects, and coordinating collaborative work. Large ecosystems such as OpenStack, which is hosted on Gerrit, receive a high volume of code changes every day, making it challenging for reviewers to decide which contributions should be handled first.

In response to this, OpenStack developers use a special review-priority label to indicate which changes are urgent or should be reviewed ahead of others. However, little is known about how consistently this label is applied, how it influences reviewer behavior, or whether it actually helps reduce review delays.

This project aims to study how developers use the review-priority label, understand the patterns behind its application, and explore how AI techniques can support and improve its effectiveness. We will mine OpenStack’s Gerrit data, extract features related to priority signals and review outcomes, and build predictive models that help teams identify when a change should be prioritized. The goal is to provide insights and AI-assisted recommendations that make priority-driven code review more consistent, reliable, and useful in large software ecosystems.

Smart Dream Home – Enhancing Housing Accessibility Through User-Centered App Innovation

Smart Dream Home is a forward-thinking startup developing an innovative mobile application designed to guide newcomers and homebuyers in Canada through every stage of the housing journey—from research and budgeting to purchase and settlement. The organization’s main activities center around designing an intuitive, data-driven digital platform that simplifies the often-overwhelming process of finding, financing, and settling into a new home. However, as a new product targeting a highly diverse and complex user base, Smart Dream Home faces a key innovation challenge: transforming raw ideas about user needs into a validated, user-friendly, and emotionally engaging experience. Traditional market research and product testing are not sufficient to capture the real challenges faced by newcomers and first-time buyers, who vary widely in digital literacy, cultural expectations, and housing priorities. This project aims to address that gap by introducing a structured user testing and customer experience research framework that integrates qualitative and quantitative insights directly into the product development cycle. The innovation lies in developing a continuous feedback and co-creation model where real users are not just test subjects but active collaborators in shaping product usability and emotional resonance. This approach goes beyond typical app development cycles, embedding empathy-driven design and behavioral insights into Smart Dream Home’s technology roadmap. To achieve this, expertise is required in marketing research, UX/UI testing methodologies, data analysis, and human-centered design, alongside strong communication skills to interpret complex feedback and translate it into actionable improvements. By developing this research-driven innovation process, Smart Dream Home will be able to refine its product with precision, increase user adoption, and position itself as a trusted digital companion for homebuyers across Canada.